Input output vectors for adaptive learning stabilizer

It would be useful if the arducopter gurus help me to understand the input parameters to NN i.e. the configuration of the copter while in flight, my understanding:

Assumption: desired Roll, Pitch and Yaw to be 0 radians and height H fixed. Not worrying about drift for this example. No external force e.g. wind. Payload might not be at GC. Actuation numbers are deltas + or -

Neural Networks for Control by Martin T. Hagan, School of Electrical & Computer Engineering, Oklahoma State University

The purpose of this tutorial is to provide a quick overview of neural networks and to explain how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorithm (including its variations) is the principal procedure for training multilayer perceptrons; it is briefly described here.

I will code the math in Mathematica to model the NN control theory and make up examples. It is much more visual and analytic than C or Python.

I will post some stuff shortly.

Ok so what we know so far is that others have done NN control for UAVs, we suspect we do not need any specialized hardware, and we suspect NN control system for Ardu family is a reality, and perhaps porting some code from here and there might start a nice prototype to test.

I am very happy with this development of events and discussions, it ignites my passion to do something new.